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The purpose of this paper is to identify the most critical antecedents of destination loyalty formation (DLF) and to develop a series of propositions for the relationships among the antecedents of loyalty formation and their direct and indirect impacts on loyalty formation.

This conceptual paper provides a comprehensive review of the previous studies that examined destination loyalty and posits a framework of tourist DLF titled Destination Loyalty Formation.

In the proposed conceptual model, the sequential relationships among the antecedents of tourist destination loyalty postulate that previous experiences are the most influential driver that could manipulate tourist destination loyalty. Place attachment and involvement constitute the second most influential factors of DLF. In addition to the above two variables, destination image is proposed to have direct and indirect effects on perception of service quality and satisfaction. Meanwhile, service quality and tourist satisfaction are proposed to have the largest magnitude of direct impacts on destination loyalty.

Previous studies examined most of the antecedents of destination loyalty separately. There is yet an effort to simultaneously consider antecedents of destination loyalty to examine how each antecedent relates to DLF. This conceptual paper attempts to address this issue by proposing a conceptual model that simultaneously considers antecedents of destination loyalty and examines how each antecedent relates to DLF.

The aim of this research work is to examine the originator which is affecting in Thailand the adoption of m-commerce (based on the behavioural intention). The usage of m-commerce has faced reluctance by the subscribers of mobile phone, which is in general the most anticipated challenge among both the developing and developed countries. Similarly, there are restricted empirical research work regarding to the m-commerce in Thailand. As a result, in the situation of developing countries (for instance, Thailand specially), very less numbers of research exist for the recognition of important variables for the m-commerce installation or estimating the m-commerce adoption variables. For explaining the behavioural targets of subscribers and for estimation generally the model that has been used is referred to as technology acceptance model (TAM). First, the factor subjective norms by the region of technology acceptance had contradictory outcomes and inconsistency to the behavioural target. In this study, we employed the Smart Partial Least Square Structural Equation Modelling version 3.2.6 as a data analysis technique. The response rate of the current study is 81%. The results have certainty that has established the presence of these associations between the users which implicated the significance of subjective norms in Thailand which were recognized. The personal opinion of usefulness, perceptions of attitude and easy usage to m-commerce are the important features towards the subjective norms which are the social impacts.

Beijing rail transit can actively control the density of rail transit passenger flow, ensure travel facilities and provide a safe and comfortable riding atmosphere for rail transit passengers during the epidemic. The purpose of this paper is to efficiently monitor the flow of rail passengers, the first method is to regulate the flow of passengers by means of a coordinated connection between the stations of the railway line; the second method is to objectively distribute the inbound traffic quotas between stations to achieve the aim of accurate and reasonable control according to the actual number of people entering the station.

This paper analyzes the rules of rail transit passenger flow and updates the passenger flow prediction model in time according to the characteristics of passenger flow during the epidemic to solve the above-mentioned problems. Big data system analysis restores and refines the time and space distribution of the finely expected passenger flow and the train service plan of each route. Get information on the passenger travel chain from arriving, boarding, transferring, getting off and leaving, as well as the full load rate of each train.

A series of digital flow control models, based on the time and space composition of passengers on trains with congested sections, has been designed and developed to scientifically calculate the number of passengers entering the station and provide an operational basis for operating companies to accurately control flow.

This study can analyze the section where the highest full load occurs, the composition of passengers in this section and when and where passengers board the train, based on the measured train full load rate data. Then, this paper combines the full load rate control index to perform reverse deduction to calculate the inbound volume time-sharing indicators of each station and redistribute the time-sharing indicators for each station according to the actual situation of the inbound volume of each line during the epidemic. Finally, form the specified full load rate index digital time-sharing passenger flow control scheme.

This paper aims to explore how the novel information technology (NIT) [1] affects three dimensions of sustainable supply chain performance (economic performance, environmental performance and social performance) and how two dimensions of IT alignment (IT infrastructure alignment and IT human resources alignment) mediate the relationship between them.

NIT is defined, the dimension of IT alignment is expanded, the theoretical hypotheses are proposed and are tested using survey data from 394 manufacturing enterprises using NIT in China.

The results indicate that NIT plays a positive role in improving sustainable supply chain performance, and IT alignment mediates the impact of NIT on sustainable supply chain performance.

This study highlights the impact of NIT on sustainable supply chain performance and demonstrates IT alignment as a mediator between them, it also provides a deeper understanding of how different dimensions of IT alignment affect sustainable supply chain performance

During rush hours, many passengers find it difficult to board the first train due to the insufficient capacity of metro vehicles, namely, left behind phenomenon. In this paper, a data-driven approach is presented to estimate left-behind patterns using automatic fare collection (AFC) data and train timetable data.

First, a data preprocessing method is introduced to obtain the waiting time of passengers at the target station. Second, a hierarchical Bayesian (HB) model is proposed to describe the left behind phenomenon, in which the waiting time is expressed as a Gaussian mixture model. Then a sampling algorithm based on Markov Chain Monte Carlo (MCMC) is developed to estimate the parameters in the model. Third, a case of Beijing metro system is taken as an application of the proposed method.

The comparison result shows that the proposed method performs better in estimating left behind patterns than the existing Maximum Likelihood Estimation. Finally, three main reasons for left behind phenomenon are summarized to make relevant strategies for metro managers.

First, an HB model is constructed to describe the left behind phenomenon in a target station and in the target direction on the basis of AFC data and train timetable data. Second, a MCMC-based sampling method Metropolis–Hasting algorithm is proposed to estimate the model parameters and obtain the quantitative results of left behind patterns. Third, a case of Beijing metro is presented as an application to test the applicability and accuracy of the proposed method.

This study investigated the mediating role of job satisfaction and the moderating role of career growth opportunity in the relationship between public service motivation (PSM) and public employees' turnover intention.

The authors recruited 587 public employees from Yunnan Province, China to test moderation and mediation hypotheses. The authors conducted confirmatory factor analysis to determine the discriminant and convergent validity of the measures of PSM, turnover intention, job satisfaction and career growth opportunity. Finally, the authors carried out bootstrapping to ascertain direct, indirect and conditional indirect effects.

PSM had a negative effect on public employees' turnover intention, but this relationship was partially mediated by job satisfaction. Career growth opportunity moderated the association between job satisfaction and turnover intention. In particular, the indirect effect of PSM on turnover intention through job satisfaction weakened under high career growth opportunities.

The results highlighted the significance of PSM and career growth opportunity in shaping public employees' work-related attitudes and behaviors. Public organizations should consider PSM a key criterion in recruitment and selection and pay more attention to the significance of intervening in career growth to satisfy public employees' psychological needs related to individual career development.

This study contributes to the literature on the disputed link between PSM and turnover intention and uncovered the underlying mechanism through which PSM affects public employees' turnover intention by proposing job satisfaction and career growth opportunity as a mediator and moderator, respectively.

High levels of stress reported at college campuses has led to the need for stress management interventions. College students often do not know how to deal with the increase in stress during college which may lead to ineffective ways to manage stress, such as drugs, alcohol, and under the worst circumstance, suicide. Several universities have implemented stress relieving centers where students can participate in various modalities to relax and reduce symptoms of stress. The purpose of this paper is to compare four stress reduction modalities on the amount of physiologic and perceived stress (PS) reduction in a stress relief center.

Archival information of 5,526 students (2,759 female, 2,767 male) were analyzed. During their time at the relaxation center, these students would participate in one of four relaxation modalities (massage chair, chi machine, rejuvenation lounger, or sitting meditation). Upon entering and exiting the center, PS, systolic blood pressure (SBP), diastolic blood pressure (DBP), and heart rate (HR) were measured. The dependent variables were compared from pre- to post-relaxation with paired tests. Gain scores were calculated for each dependent variable and compared between modalities with an ANOVA and post hoc independent t-tests. The α was set at=0.05 for statistical significance.

Results indicated that all four modalities showed an overall decrease in stress-related symptoms for both men and women (p<0.05). There was no statistical difference in dependent variable gain scores between the relaxation modalities (p>0.05) for men. There was no statistical difference in dependent variable gain scores between the relaxation modalities (p>0.05) for women except for SBP and DBP where the massage chair, chi machine, and sitting meditation all reduced SBP and DBP to a greater degree than the rejuvenation lounger (p<0.05).

The results of this study suggest that the use of these stress reduction modalities (massage chair, chi machine, rejuvenation lounger, or sitting meditation) is effective at transiently reducing physiologic and perceived measures of stress of college students. Universities should recognize the importance of stress relief centers in order to help students manage stress symptoms and effectively manage their daily stress levels.

Different external supply scenarios faced by the retailers will affect their choice of strategy when supply is disrupted and becomes far less than demand, urgently. This study focuses on analyzing both demand and supply side response strategies to meet customer demand and reduce the impact of the shortage during supply disruptions.

According to the quantity of products that the external market can provide, the external supply scenarios were divided into sufficient-type external supply and learning-type external supply. A two-echelon perishable goods supply chain was analyzed, and three kinds of contingency strategy models for downstream retailers were investigated. First, in the sufficient external supply scenario, the optimal price and transshipment quantity to maximize retailer's profits is discussed. Second, in the scenario of learning-type external supply, this study analyzes the optimal decision in three mechanisms of the hybrid strategy and their application: price priority mechanism, quantity priority mechanism and price–quantity balance mechanism. Furthermore, the influence of penalty cost and supply on the priority orders of different mechanisms was studied.

Results show that comparing the two pure strategies (pricing strategy and transshipment strategy)it was noted that the hybrid strategy produces the best results in sufficient-type external supply scenario. In the learning-type external supply scenario, a numerical study has shown the existence of three areas in case of penalty cost and supplier's capacity, and each areas has different priority orders of the three mechanisms. Under the situation of learning external supply, the retailer's optimal strategy is affected by parameters such as penalty cost and supply volume.

The main innovation of the work lies in the following: First; the external supply situation was divided into sufficiency type and learning type, which improves the external situation faced by retailers after the outbreak of emergencies, helps retailers understand the external situation, conforms to the actual situation and has certain practical application value. Second; in the context of learning external supply, there are three coping strategies for retailers, including: Price priority mechanism, Quantity priority mechanism and Pricing and transshipment balance mechanism. This will help retailers make strategic choices, make more scientific management decisions and improve the supply chain emergency management theory. Third; the demand side response was managed through the change of external supply during supply side recovery period and supply disruption. The proposed model enables managing and analyzing supply disruption efficiently and effectively via handling uncertainty by considering all aspects of decision-making process. The proposed model can be applied in various fields such as vegetable and fruit, fresh food, etc.

The purpose of this paper is to study the influences of the oil film thickness between the friction pairs, the rotational speed of the active and passive friction disks and the inlet pressure of the lubricant on the transmission efficiency.

A mathematical model of transmission efficiency was established, and the efficiency of transmission was studied by means of numerical analysis.

The results demonstrate that the transmission efficiency decreases with the thickness of the oil film increases. When the thickness of oil film d = 0.1 mm, the relationship between transmission efficiency and transmission ratio is linear, that is, with the transmission ratio increases, the transmission efficiency also increases which does not change with the inlet pressure changes. However, when d = 0.1 mm, their relationship is non-linear; the efficiency increases first and then decreases as the transmission ratio increases, but decreases as the inlet pressure increases.

The authors obtained a rule is that increasing the rotational speed and reducing the inlet pressure of the lubricating oil can improve the transmission efficiency. This study can provide a theoretical basis for power transmission designing of hydro-viscous clutch.